3.9 Article

Time to Assess Bias in Machine Learning Models for Credit Decisions

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Review Physics, Multidisciplinary

Explainable AI: A Review of Machine Learning Interpretability Methods

Pantelis Linardatos et al.

Summary: Recent advances in artificial intelligence have led to widespread industrial adoption, with machine learning systems demonstrating superhuman performance. However, the complexity of these systems has made them difficult to explain, hindering their application in sensitive domains. Therefore, there is a renewed interest in the field of explainable artificial intelligence.

ENTROPY (2021)

Article Social Sciences, Mathematical Methods

Using First Name Information to Improve Race and Ethnicity Classification

Ioan Voicu

STATISTICS AND PUBLIC POLICY (2018)

Proceedings Paper Computer Science, Software Engineering

Fairness Definitions Explained

Sahil Verma et al.

2018 IEEE/ACM INTERNATIONAL WORKSHOP ON SOFTWARE FAIRNESS (FAIRWARE 2018) (2018)

Article Business, Finance

Does Credit Scoring Produce a Disparate Impact?

Robert B. Avery et al.

REAL ESTATE ECONOMICS (2012)

Article Mathematical & Computational Biology

Visualizing and assessing discrimination in the logistic regression model

Patrick Royston et al.

STATISTICS IN MEDICINE (2010)

Article Health Care Sciences & Services

Using the Census Bureau's surname list to improve estimates of race/ethnicity and associated disparities

Marc N. Elliott et al.

HEALTH SERVICES AND OUTCOMES RESEARCH METHODOLOGY (2009)